India vs Indonesia: Dimension 2.2: Online access - Non-Proprietary format Score
India
0.967
in 2023
Indonesia
0.983
in 2023
India rank
30th
Indonesia rank
27th
Dimension 2.2: Online access - Non-Proprietary format Score over time
- India
- Indonesia
How they compare
Indonesia currently reports 0.983 against 0.967 in India, a difference of 0.016.
The two have swapped places 2 times across 9 shared years of data; in 2015 it was Indonesia ahead.
India ranks 30th and Indonesia ranks 27th of 177 countries.
Across the 2 decades both report, India averaged higher in 1 and Indonesia in 1.
Head to head by decade
| Decade | India | Indonesia | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 0.6014 | 0.5586 | 0.0428 | India |
| 2020s | 0.9585 | 0.9675 | 0.009 | Indonesia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher dimension 2.2: online access - non-proprietary format score, India or Indonesia?
- Indonesia, at 0.983 against 0.967 in India as of 2023.
- What is the difference in dimension 2.2: online access - non-proprietary format score between India and Indonesia?
- 0.016, with Indonesia ahead.
- How many years of comparable data are there for India and Indonesia?
- 9 years are reported by both, from 2015 to 2023.
- How do India and Indonesia rank globally for dimension 2.2: online access - non-proprietary format score?
- India ranks 30th and Indonesia ranks 27th of 177 countries.
- Where does this data come from?
- Open Data Watch, published as Dimension 2.2: Online access - Non-Proprietary format Score. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
This openness element measures whether data are made available in nonproprietary formats. Nonproprietary file formats are important because they allow users to access data without requiring the use of a costly, proprietary software that may prevent some users from accessing the data. Common nonproprietary formats include PDF, HTML, XLSX, DOCX, CSV, and JSON files.